自适应控制的神经模糊结构

[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI:10.1109/FUZZY.1992.258715

L. Pavel, M. Chelaru

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引用次数: 13

摘要

研究了具有未知动力学特性的线性和非线性系统的跟踪控制问题。基于M. Sugeno的模糊系统模型(1985)和前馈神经网络的使用，提出了一种自调谐神经模糊自适应控制体系结构。对控制回路进行了描述。然后，将Sugeno模糊推理系统模型的自适应神经版本插入到该回路中。对该算法进行了离散时间线性和非线性系统的仿真和测试。

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Neural fuzzy architecture for adaptive control

The authors address the tracking control of linear and nonlinear systems with unknown dynamics. A self-tuning neural fuzzy adaptive control architecture, based on M. Sugeno's model for fuzzy systems (1985) and on the use of feedforward neural networks is proposed. The control loop is described. Then, the adaptive neural version of the Sugeno model for fuzzy inference systems, inserted in this loop, is presented. The algorithm was simulated and tested for discrete-time linear and nonlinear systems.<>

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[1992 Proceedings] IEEE International Conference on Fuzzy Systems

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